/*=========================================================================

  Program:   ORFEO Toolbox
  Language:  C++
  Date:      $Date$
  Version:   $Revision$


  Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
  See OTBCopyright.txt for details.


     This software is distributed WITHOUT ANY WARRANTY; without even
     the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
     PURPOSE.  See the above copyright notices for more information.

=========================================================================*/

#include "otbImage.h"
#include "otbImageFileReader.h"
#include "otbImageFileWriter.h"
#include "itkNeighborhoodAlgorithm.h"
#include <math.h>

// Software Guide : BeginLatex
//
// This example uses \doxygen{itk}{ShapedNeighborhoodIterator} to implement a binary
// erosion algorithm.  If we think of an image $I$ as a set of pixel indices,
// then erosion of $I$ by a smaller set $E$, called the \emph{structuring
// element}, is the set of all indices at locations $x$ in $I$ such that when
// $E$ is positioned at $x$, every element in $E$ is also contained in $I$.
//
// This type of algorithm is easy to implement with shaped neighborhood
// iterators because we can use the iterator itself as the structuring element
// $E$ and move it sequentially through all positions $x$.  The result at $x$
// is obtained by checking values in a simple iteration loop through the
// neighborhood stencil.
//
// We need two iterators, a shaped iterator for the input image and a regular
// image iterator for writing results to the output image.
//
// Software Guide : EndLatex

// Software Guide : BeginCodeSnippet
#include "itkConstShapedNeighborhoodIterator.h"
#include "itkImageRegionIterator.h"
// Software Guide : EndCodeSnippet

int main(int argc, char * argv[])
{
  if (argc < 4)
    {
    std::cerr << "Missing parameters. " << std::endl;
    std::cerr << "Usage: " << std::endl;
    std::cerr << argv[0]
              << " inputImageFile outputImageFile element_radius"
              << std::endl;
    return -1;
    }

  // Software Guide : BeginLatex
  //
  // Since we are working with binary images in this example, an \code{unsigned
  // char} pixel type will do.  The image and iterator types are defined using
  // the pixel type.
  //
  // Software Guide : EndLatex

  // Software Guide : BeginCodeSnippet
  typedef unsigned char            PixelType;
  typedef otb::Image<PixelType, 2> ImageType;

  typedef itk::ConstShapedNeighborhoodIterator<
      ImageType
      > ShapedNeighborhoodIteratorType;

  typedef itk::ImageRegionIterator<ImageType> IteratorType;
  // Software Guide : EndCodeSnippet

  typedef otb::ImageFileReader<ImageType> ReaderType;
  ReaderType::Pointer reader = ReaderType::New();
  reader->SetFileName(argv[1]);

  try
    {
    reader->Update();
    }
  catch (itk::ExceptionObject& err)
    {
    std::cout << "ExceptionObject caught !" << std::endl;
    std::cout << err << std::endl;
    return -1;
    }

  ImageType::Pointer output = ImageType::New();
  output->SetRegions(reader->GetOutput()->GetRequestedRegion());
  output->Allocate();

// Software Guide : BeginLatex
//
// Refer to the examples in Section~\ref{sec:itkNeighborhoodIterator} or the
// source code of this example for a description of how to read the input image
// and allocate a matching output image.
//
// The size of the structuring element is read from the command line and used
// to define a radius for the shaped neighborhood iterator.  Using the method
// developed in section~\ref{sec:itkNeighborhoodIterator} to minimize bounds
// checking, the iterator itself is not initialized until entering the
// main processing loop.
//
// Software Guide : EndLatex

// Software Guide : BeginCodeSnippet
  unsigned int                               element_radius = ::atoi(argv[3]);
  ShapedNeighborhoodIteratorType::RadiusType radius;
  radius.Fill(element_radius);
// Software Guide : EndCodeSnippet

// Software Guide : BeginLatex
//
// The face calculator object introduced in
// Section~\ref{sec:NeighborhoodExample3} is created and used as before.
//
// Software Guide : EndLatex

// Software Guide : BeginCodeSnippet
  typedef itk::NeighborhoodAlgorithm::ImageBoundaryFacesCalculator<
      ImageType> FaceCalculatorType;

  FaceCalculatorType                         faceCalculator;
  FaceCalculatorType::FaceListType           faceList;
  FaceCalculatorType::FaceListType::iterator fit;

  faceList = faceCalculator(reader->GetOutput(),
                            output->GetRequestedRegion(),
                            radius);
// Software Guide : EndCodeSnippet

// Software Guide : BeginLatex
//
// Now we initialize some variables and constants.
//
// Software Guide : EndLatex

// Software Guide : BeginCodeSnippet
  IteratorType out;

  const PixelType background_value = 0;
  const PixelType foreground_value = 255;
  const float     rad = static_cast<float>(element_radius);
// Software Guide : EndCodeSnippet

// Software Guide : BeginLatex
//
// The outer loop of the algorithm is structured as in previous neighborhood
// iterator examples.  Each region in the face list is processed in turn.  As each new
// region is processed, the input and output iterators are initialized on that
// region.
//
// The shaped iterator that ranges over the input is our structuring element
// and its active stencil must be created accordingly.  For this example, the
// structuring element is shaped like a circle of radius
// \code{element\_radius}.  Each of the appropriate neighborhood offsets is
// activated in the double \code{for} loop.
//
// Software Guide : EndLatex

// Software Guide : BeginCodeSnippet
  for (fit = faceList.begin(); fit != faceList.end(); ++fit)
    {
    ShapedNeighborhoodIteratorType it(radius, reader->GetOutput(), *fit);
    out = IteratorType(output, *fit);

    // Creates a circular structuring element by activating all the pixels less
    // than radius distance from the center of the neighborhood.

    for (float y = -rad; y <= rad; y++)
      {
      for (float x = -rad; x <= rad; x++)
        {
        ShapedNeighborhoodIteratorType::OffsetType off;

        float dis = ::sqrt(x * x + y * y);
        if (dis <= rad)
          {
          off[0] = static_cast<int>(x);
          off[1] = static_cast<int>(y);
          it.ActivateOffset(off);
          }
        }
      }
// Software Guide : EndCodeSnippet

// Software Guide : BeginLatex
//
// The inner loop, which implements the erosion algorithm, is fairly simple.
// The \code{for} loop steps the input and output iterators through their
// respective images.  At each step, the active stencil of the shaped iterator
// is traversed to determine whether all pixels underneath the stencil contain
// the foreground value, i.e. are contained within the set $I$.  Note the use
// of the stencil iterator, \code{ci}, in performing this check.
//
// Software Guide : EndLatex

// Software Guide : BeginCodeSnippet
    // Implements erosion
    for (it.GoToBegin(), out.GoToBegin(); !it.IsAtEnd(); ++it, ++out)
      {
      ShapedNeighborhoodIteratorType::ConstIterator ci;

      bool flag = true;
      for (ci = it.Begin(); ci != it.End(); ci++)
        {
        if (ci.Get() == background_value)
          {
          flag = false;
          break;
          }
        }
      if (flag == true)
        {
        out.Set(foreground_value);
        }
      else
        {
        out.Set(background_value);
        }
      }
    }
// Software Guide : EndCodeSnippet

  typedef otb::ImageFileWriter<ImageType> WriterType;

  WriterType::Pointer writer = WriterType::New();
  writer->SetFileName(argv[2]);
  writer->SetInput(output);
  try
    {
    writer->Update();
    }
  catch (itk::ExceptionObject& err)
    {
    std::cout << "ExceptionObject caught !" << std::endl;
    std::cout << err << std::endl;
    return -1;
    }

  return EXIT_SUCCESS;
}
